I am fascinated by the term ‘new media,’ which grants a stiff nod to the elusive and ever-changing concept of “new,” while focusing on what is en vogue in the moment as the relevant bit. All other media is quaint, old-fashioned, and decidedly outdated. Possibly of interest to a collector, nestled among a of curiosities in a museum display, or adding a bit of vintage flair to the home of a hipster, these passe items have been relegated to past lives and past ways of interacting with the world. In the introduction to New Media: 1740-1915, editors Lisa Gitelman and Geoffrey B. Pingree think about what “new media” would have looked like for previous generations before listing a variety of well-known forms of extinct media: “typewriters, vinyl record albums, eight-track magnetic tapes, and the like.” Their point? “These are, from our current standpoint, old media. But they were not always old, and studying them in terms that allow us to understand what it meant for them to be new is a timely and culturally important….All media were once ‘new media,’ and our purpose in these essays is to consider such emergent media within their historical contexts – to seek out the past on its own passed terms” (xi).

Gitelman and Pingree make a good point here, and remind us to consider these media not from our own backward-looking contexts – the perspective that views them as quaint and old-fashioned – but from the prospect of those to whom this media really was new. 3Dimagery, programmable machines (such as the Jacquard loom, which I wrote about previously), electric messaging, recordedsound files, and social networks are not the products of the last forty years.

Take the Fiske Reading Machine (pictured above), for example. This reading machine is a roaring ’20s era personal reader that was designed for portability, and marketed using the same arguments for portability that tablet makers use today. The idea seems like it was somewhat ahead of its time, but the increasing mobility afforded the public via railroads and automobiles must have increased the demand for portable reading material. According to the explanatory article (linked previously, and well worth reading), the machine used ordinary typewritten copy photographically reduced to 1/100 of the original size. It required no additional power consumption – no batteries or electrical charge – apart from its fabrication and production of the proprietary texts, and reportedly would decrease paper usage if widely adopted. Economic (uses fewer resources), portability (easily carried and cheaply mailed) and accessibility (encyclopedias, Shakespeare, and the Bible available for a fraction of the cost of traditional books) issues are touted as benefits of the machine.

Of course, the Fisk machine faded into cultural memory (I cannot imagine why; how would you have looked at the man in the next seat who was squinting into the tiny viewer of this device?), but other ways of producing and re-producing texts arose in the 20th century. From handwritten drafts to typewritten copy, and eventually to the word processor and personal computer, the process of producing books has changed.

Matthew Kirschenbaum’s article “The Book-Writing Machine: What was the first novel ever written on a word processor?” discusses one of these technological changes: the creation of Len Deighton’s WWII-era technothriller, Bomber. Produced on a word processor, IBM’s MTST (Magnetic Tape Selectric Typewriter) and published in 1970, the mechanized experience changed Deighton’s method of editing from cutting, rearranging, and pasting sections of his manuscript – with scissors and paste – to editing them via the re-codeable magnetic tape. This particular seminal model cost $10,000 (or $65,000 in today’s economy), weighted 200 pounds, had no screen, and could print at the lightening-fast speed of 150 wpm. (At that rate, printing out the text from this single post would take 11 minutes.)

But although Deighton states that “One might almost think the word processor (as it was eventually named) was built to my requirements,” not everyone so easily adapted to mechanized production of their literary work. In her article “Russell Banks’ Real-Time Notes on Adjusting the the Word Processor,” Rebecca Onion tells us that “Banks was dubious about his relationship with the technology, saying that the ‘simple mechanics of the task’ were problematic. The experience was ‘an unfamiliar mixture of speed and slowdown.’ But his biggest issue with the new way of writing was the immateriality of the process: ‘Since there is no object, no product on paper emerging as I go, there seems to be no activity.'” Banks’ comment is telling. Previously, writers had a physical artifact that provided evidence of their industry: pages of handwritten manuscript or a stack of typewritten sheets. The predecessors of our modern word processing programs did not have the fancy tools that we do now: word counts, number of pages, and easy navigability have all been added in the interim. The earliest processors were electric typewriters with small screens similar to what would be found on a standard calculator. Block characters would fill the rectangular display squares and race by as one typed, showing a phrase at a time on the tiny screen, and storing the rest in its tiny memory. If mistakes were made, one could carefully backspace to it, one character at a time, and fix it, before continuing on. Writing in this way would make the text seem ephemeral, and reviewing or judging the quantity of writing done was difficult. A quick tap of the “enter” key and the printing would start, scrolling through the perforated pages connected to one another like a roll of paper towels. In his remarks, Banks mourns the loss of the physical artifacts produced by previous methods of composition, and he has difficulty reconciling the virtual representation of his work with his previous mode of production. He describes this transition as a “transformation from word inscriber to processor.” This admission reveals that his view of himself has changed from one who inscribes, prints, and marks words on a page to a mechanized processor, a human machine that runs on a program and produces words.

This relationship between human and machine has evolved and become more intuitive as machines become almost extensions of ourselves. Lightweight laptop computers, tablets, and especially smart phones have become omnipresent. In his Wall Street Journal article “The Science Behind Guessing What You’ll Type Next,” Matthew Lynley looks at the science behind predictive typing programs. He explains that “typing has evolved into a whole field of science called ‘natural language processing,’ teaching computers to understand how human language works. It’s a field that mobile-device makers are keenly interested in, because it improves the user experience of the phone — leading to selling more phones.” The android program discussed uses a language modeling program that infers from a string of words which word is likely to come next using probability predictions based on the data collected from user interface with a touch screen. The goal of such programs is to eliminate as much interference as possible between human and machine, allowing for a more intuitive and streamlined process.

This streamlining of interactions between people and programmed machines by predicting and encoding human behavior is also seen in the resources we access via the internet. Jennifer Howard discusses the two-way communication phenomenon that allows programs to learn from people in her Chronicle of Higher Education article “In the Digital Era Our Dictionaries Read Us.” She explains that “with the spread of digital technologies, dictionaries have become a two-way mirror, a record not just of words’ meanings but of what we want to know. Digital dictionaries read us.” Now unlike me, not everyone has a dictionary at hand at all times. I consider myself to be a bit unusual in this regard. I love dictionaries. And thesauruses. (Say that word three times fast: thesauruses, thesauruses, thesauruses. If you do not know what a thesaurus is, here’s a dictionary definition, although if you read this blog I suspect you might be a logophile like me.) I have a dictionary/thesaurus app on my phone, and I often use the OED to ferret out the etymology and evolution of a particular word. But dictionaries are all around us, not just available in that book that resides on your shelf, or through a website or app. Howard explains that “whenever you send a text or an e-mail, or read an e-book on your Nook, Kindle, or iPad, a dictionary is at your fingertips, whether or not you’re aware of it.” Many tablet readers have functions that allow the reader to highlight a word, then choose to look it up in a dictionary, on Wikipedia, or perform a google search. These lookups, including unsuccessful ones or those that yield unsatisfactory results can now be tracked, and electronic dictionaries can be adapted to suit users’ needs.

The editor-in-chief of Macmillan Education favors online dictionaries and is no longer publishing printed versions, but Howard contradicts this “argument that digital is ideal for dictionaries, no medium is perfect. Print offers pleasures that pixels don’t. It’s hard to electronically recreate the joy of browsing a printed page of definitions and ‘finding something you didn’t know you were looking for,’ Martin [head of U.S. Dictionaries for Oxford University Press] says. Dictionary makers are working on electronic simulacra. If you’re using the Merriam-Webster phone app, for instance, you can turn your device horizontally and get a scrolling list of words that mimics browsing in the vicinity of a word in a print dictionary.” Realizing and acknowledging what has been lost in the transition from printed page to digital app, Merriam-Webster has adapted its phone app functionality to mimic one of the lost aspects of physical interaction with a book. Like the language modeling programs designed to intuit what users will type next, digital dictionaries are also adapting to meed users’ needs and preferences by taking the material evidence of human-machine interactions (encoded data) and using it to predict and encode human behavior patterns.